结合深度学习和图割法的遥感影像建筑物检测     

刘舸  邓兴升 《测绘通报》2019,(11):69-73

提出一种基于卷积神经网络和图割法的自动提取高分影像建筑物的方法。首先，通过卷积神经网络定位与检测建筑物的位置，逐一提取单个建筑物轮廓，利用检测结果分别建立建筑物和非建筑物的高斯混合模型（GMM），然后结合最大流最小割的图像分割方式实现全局优化，完成建筑物初步提取，最后用形态学进行优化。通过试验证明了该方法的可行性。  相似文献   

深度学习GoogleNet模型支持下的中分辨率遥感影像自动分类     

陈斌  王宏志  徐新良  王首泰  张亚庆 《测绘通报》2019,(6):29-33,40

提出了一种基于深度学习技术的遥感分类方法，它能有效解决中分辨率影像在分类过程中出现的像元混分问题。研究选用2016年5月12日武汉市Landsat 7 ETM+遥感影像，基于GoogleNet模型中的Inception V3网络结构，借助迁移学习方法，构建出遥感分类模型，实现了对武汉市主城区4类典型地物（不透水层、植被、水体和其他用地）的自动分类提取，并将分类结果与传统最大似然分类（ML）结果进行了对比分析。研究表明：基于深度学习方法的遥感影像总体分类精度高达88.33%，Kappa系数为0.834 2，明显优于传统ML方法总体分类精度83%和Kappa系数0.755 0，而且有效抑制了地物在分类过程中出现的像元混分现象。  相似文献   

地灾监测的大数据信息平台研究及应用     

何伟  张伦宁  贺成成  梁霄  宋连凯 《测绘通报》2019,(1):127-131

重点对地灾监测方面的方案研究进行了阐述，在构建大数据信息平台的设计方案时，以实现高度自动化的全方位监测功能为导向，依托导航卫星数据接收机和多源传感器，集成构建大数据信息平台的系统解决方案，主要包括扼流圈卫星天线、GNSS数据接收机、MEMS传感器、环境测量单元、防雷区域单元等功能元件的组成、多传感器的系统集成，以及全方位监测的功能实现。按照地灾监测大数据信息平台建设、构建大数据平台关键技术突破及检测数据解算软件功能实现的顺序，完成了GNSS实时监测预警应用网络系统HCmonitor的研发。综合应用多种手段实现地灾监测的功能升级，为解决重大灾害预警提供了新的思路和解决方案，该项成果在甘肃舟曲的灾后重建工程得到应用与推广。  相似文献   

新工科理念下的实验课程教学改革与实践探索     

蔡剑红  霍亮  朱凌 《测绘通报》2019,(2):147-152

近年来为适应创新人才的培养，"卓越计划"开启了全新教学模式。基于新工科理念，为了更好地进行实验课程教学，以"3ds Max软件三维建模"为例，笔者从课程内容安排、教学方式、考核机制等方面进行了教学探索和实践。本文以应用软件实验类课程项目教学的实践经验为基础，注重学生团队合作和交流能力、实践能力、创新能力培养，以及多渠道快速学习新事物的能力，通过与测绘新技术下多软件融合，使学生拥有知识整合能力，为提高实践教学提供参考和借鉴，以更好地适应新工科理念下的创新人才培养。  相似文献   

大跨径斜拉桥主梁线形测控新方法研究及应用     

顾玄龙  刘成龙  李雷  沈卢明  蒋涛  杨雪峰 《测绘通报》2019,(4):49-53,59

大跨径斜拉桥结构刚度小、变形大，为保证主梁顺利合龙，施工过程必须快速精确定位主梁上各个节段的平面和竖向线形。区别于传统的极坐标主梁平面线形测控方法，本文提出采用全站仪自由设站法测控主梁平面线形；同时区别于传统的水准测量方法，提出采用全站仪间接高差传递的方法测控主梁竖向线形。介绍了两种新方法的测量原理，通过工程实例论证了新方法的可行性和实用性，且能够大幅度提高测控效率，可为其他大跨径桥梁主梁线形的测控提供一定的参考。  相似文献   

Semantic segmentation of high spatial resolution images with deep neural networks     

Haiping Yang  Jiancheng Luo  Fang Chen 《地理信息系统科学与遥感》2019,56(5):749-768

Availability of reliable delineation of urban lands is fundamental to applications such as infrastructure management and urban planning. An accurate semantic segmentation approach can assign each pixel of remotely sensed imagery a reliable ground object class. In this paper, we propose an end-to-end deep learning architecture to perform the pixel-level understanding of high spatial resolution remote sensing images. Both local and global contextual information are considered. The local contexts are learned by the deep residual net, and the multi-scale global contexts are extracted by a pyramid pooling module. These contextual features are concatenated to predict labels for each pixel. In addition, multiple additional losses are proposed to enhance our deep learning network to optimize multi-level features from different resolution images simultaneously. Two public datasets, including Vaihingen and Potsdam datasets, are used to assess the performance of the proposed deep neural network. Comparison with the results from the published state-of-the-art algorithms demonstrates the effectiveness of our approach.  相似文献   

A literature synthesis of LiDAR applications in transportation: feature extraction and geometric assessments of highways     

Suliman A. Gargoum  Karim El Basyouny 《地理信息系统科学与遥感》2019,56(6):864-893

Interest in using Light Detection and Ranging (LiDAR) technology in Transportation Engineering has grown over the past decade. The high accuracy of LiDAR datasets and the efficiency by which they can be collected has led many transportation agencies to consider mobile LiDAR as an alternative to conventional tools when surveying roadway infrastructure. Nonetheless, extracting semantic information from LiDAR datasets can be extremely challenging. Although extracting roadway features from LiDAR has been considered in previous research, the extraction of some features has received more attention than others. In fact, for some roadway design elements, attempts to extract those elements from LiDAR have been extremely scarce. To document the research that has been done in this area, this paper conducts a thorough review of existing studies while also highlighting areas where more research is required. Unlike previous research, this paper includes a thorough review of the previous attempts at data extraction from LiDAR while summarizing the detailed steps of the extraction procedure proposed in each study. Moreover, the paper also identifies common tools and techniques used to extract information from LiDAR for transportation applications. The paper also highlights common limitations in existing algorithms that could be improved in future research. This paper represents a valuable resource for researchers and practitioners interested in knowing the current state of research on the applications of LiDAR in the field of Transportation Engineering while also understanding the opportunities and challenges that lie ahead.  相似文献   

Effects of heavy metal pollution on farmland soils and crops: A case study of the Xiaoqinling Gold Belt,China   总被引：1，自引：0，他引：1  

《China Geology》2020,3(3):402-410

This paper focuses on the heavy metal enrichment and heavy metal pollution degree associated with mining activities in some crops and the soils of different parent materials in the Xiaoqinling Gold Belt. According to the geochemical analysis results of the soils observed in the gold belt, the soils are most highly enriched in Pb, followed by Cr, Cu, and Zn. Furthermore, they are relatively poor in Hg, Cd, and As. It is also shown that the heavy metals in all kinds of soils have the same geochemical characteristics in the gold belt. As for the crops (such as corn and wheat) in the gold belt, Zn and Cu are the most abundant elements, followed by Pb and Cr. Meanwhile, Hg, Cd, and As were found to have relatively low concentrations in the crops. The heavy metals in wheat and corn have the same geochemical characteristics in the gold belt in general. Compared to the aeolian loess soils and the crops therein, heavy metals are more enriched in diluvial and alluvial soils and the crops therein. As shown by relevant studies, the Hg, Pb, Cd, Cu, and Zn pollution are mainly caused by mining activities. Corn and wheat in the gold belt have a high tendency of risk exposure to heavy metal pollution since they are mostly affected by mining activities and feature high background values of heavy metal concentrations. Furthermore, wheat is more liable to be enriched in heavy metals than corn is grown in all types of soils. The Hg pollution in soils leads to Hg accumulation, increasing the risk of Hg uptake in crops, and further affecting human health. This study will provide a scientific basis for the control and management of heavy metals in farmland soils of mining areas.  相似文献   

西秦岭甘南地区上二叠统毛毛隆组古环境演变:基于遗迹网络分析          下载免费PDF全文

党志英  张立军 《古地理学报》2020,22(6):1171-1180

西秦岭地区是二叠系—三叠系之交深水相保存较为连续的地区,西秦岭甘南地区上二叠统毛毛隆组发育丰富的遗迹化石(12属17种)。遗迹网络分析作为新兴的研究方法,侧重于用相互连接的遗迹分类群来重建遗迹群落系统,这为研究遗迹群落的行为学和生态学提供了丰富的手段。笔者以西秦岭甘南地区上二叠统毛毛隆组发现的遗迹化石为数据源,运用遗迹网络分析方法,揭示出毛毛隆组遗迹群落具结构化特征,遗迹群落体现出环境驱动的遗迹组合面貌特征: Palaeophycus-Lockeia-Arenicolites-Dictyodora-Planolites-Protovirgularia-Chondrites组合(C1,近源浊流区),Palaeophycus-Lockeia-Arenicolites-Dictyodora-Protovirgularia-Phycodes-Chondrites-Helminthopsis组合(C2,浊流过渡区—浊流远源区),和Palaeophycus-Nereites-Scolicia-Protovirgularia-Helminthopsis组合(C3,远源浊流区)。该遗迹群落由C1演变至C3的过程,揭示了古环境从近源浊流区至远源浊流区的演变历程。  相似文献   

山西阳泉地区旅游地质资源遥感调查与成果分析     

王浩乾  王明明  刘安  郭政斌  王波涛 《中国地质调查》2020,7(6):96-102

为查清山西省阳泉地区旅游地质资源分布状况,方便当地政府掌握区内旅游地质资源现状,为地质公园开发、保护与发展规划提供决策依据,山西省自然资源厅(原山西省国土资源厅)于2018年开展了“山西省阳泉地区旅游地质资源调查”项目,基于三维可视化遥感影像,采用目视解译方法,并结合已有地质资料和野外调查数据,获取了阳泉旅游地质资源分布信息。在阳泉中东部圈定了一条呈月牙形的旅游地质资源密集分布带,该分布带西起盂县藏山,向南东过平定玉皇洞,终至平定县娘子关,分布在碳酸盐岩区,集山地地貌景观、岩溶地貌景观和泉域地貌景观于一体,是我国北方地区规模较大、较为典型的碳酸盐岩地貌、岩溶地貌和泉域地貌出露区,在区域上连片分布,具有较高的开发潜力。建议在“藏山旅游区—岩溶地貌景区—娘子关旅游区”范围申请建立北方碳酸盐岩景观多成因类型地质公园。  相似文献